The use of engineered nanopores as sensing elements for chemical and biological agents is a rapidly developing area. The distinct signatures of nanopore-nanoparticle lend themselves to statistical analysis. As a result, processing of signals from these sensors is gaining importance, but this field is relatively less developed. In this paper we demonstrate a neural network approach to classify and interpret nanopore and ion-channel signals.
Bharatan Konnanath, Prasanna Sattigeri, Trupthi Ma